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hello

Generate a greeting message within the Desmos MCP Server environment for mathematical visualization and analysis workflows.

Instructions

A simple tool that returns a greeting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoWorld

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'hello' tool implementation: a simple greeting function that takes an optional 'name' parameter (defaults to 'World') and returns a formatted greeting string. Registered via @mcp.tool() decorator.
    @mcp.tool()
    def hello(name: str = "World") -> str:
        """A simple tool that returns a greeting."""
        return f"Hello, {name}!"
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It states the tool returns a greeting but doesn't disclose any behavioral traits like whether it's idempotent, has side effects, or what the output format is. The description is minimal and lacks context beyond the basic action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's appropriately sized for such a simple tool and front-loads the core purpose clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 optional parameter) and the presence of an output schema, the description is complete enough for basic understanding. However, it could benefit from slightly more context about the greeting format or usage scenarios to be fully comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter with 0% description coverage, but the description doesn't mention parameters at all. Since there's only one parameter and the tool is very simple, the baseline is high. However, the description doesn't add meaning beyond the schema, so it doesn't fully compensate for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'returns a greeting', which is a clear purpose but vague about what kind of greeting or how it's generated. It doesn't differentiate from sibling tools (like analyze_formula or plot_math_function), but the purpose is understandable albeit basic.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any context, prerequisites, or exclusions, leaving the agent to infer usage based on the simple purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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